class_docstr: Class that collects and stores information and statistics on issues found in a dataset.
  
  Parameters
  ----------
  data :
      The data object for which the issues are being collected.
  strategy :
      Strategy used for processing info dictionaries.
  
  Attributes
  ----------
  issues : pd.DataFrame
      Stores information about each individual issue found in the data,
      on a per-example basis.
  issue_summary : pd.DataFrame
      Summarizes the overall statistics for each issue type.
  info : dict
      A dictionary that contains information and statistics about the data and each issue type.
docstr: Set the health score for the dataset based on the issue summary.
  
  Currently, the health score is the mean of the scores for each issue type.
docstr_tok: ["Set","the","health","score","for","the","dataset","based","on","the","issue","summary",".","Currently",",","the","health","score","is","the","mean","of","the","scores","for","each","issue","type","."]
code: def set_health_score(self) -> None:
      """Set the health score for the dataset based on the issue summary.
  
      Currently, the health score is the mean of the scores for each issue type.
      """
      self.info["statistics"]["health_score"] = self.issue_summary[
          "score"
      ].mean()
  
imports: from __future__ import annotations
  import warnings
  from abc import ABC, abstractmethod
  from typing import TYPE_CHECKING, Any, Dict, List, Optional, Union
  import numpy
  import pandas
label_desc: Use image node_id 11 for calling the DataIssues obj's underlying member method code with example usage: obj.set_health_score() without return types